bayesline.api.equity.XSigmaRhoMeasureSettings#
- pydantic model bayesline.api.equity.XSigmaRhoMeasureSettings#
Settings for X-Sigma-Rho measure.
This class defines settings for an X-Sigma-Rho measure, which provides exposure, volatility, correlation, and contribution data.
Show JSON schema
{ "title": "XSigmaRhoMeasureSettings", "description": "Settings for X-Sigma-Rho measure.\n\nThis class defines settings for an X-Sigma-Rho measure,\nwhich provides exposure, volatility, correlation, and contribution data.", "type": "object", "properties": { "type": { "const": "XSigmaRho", "default": "XSigmaRho", "title": "Type", "type": "string" }, "rescale_bench": { "default": true, "description": "Rescale the benchmark holdings to sum to the sum of the holdings.", "title": "Rescale Bench", "type": "boolean" }, "normalize_holdings": { "default": true, "description": "Make holdings sum to one.", "title": "Normalize Holdings", "type": "boolean" }, "analytics_space": { "default": "absolute", "description": "Compute the analytics in `absolute` space, `active` space, or compute the analytics only on the `benchmark`.", "enum": [ "absolute", "active", "benchmark" ], "title": "Analytics Space", "type": "string" } }, "additionalProperties": false }
- Config:
frozen: bool = True
extra: str = forbid
- Fields:
analytics_space (Literal['absolute', 'active', 'benchmark'])normalize_holdings (bool)rescale_bench (bool)type (Literal['XSigmaRho'])
- field type: Literal['XSigmaRho'] = 'XSigmaRho'#
- field rescale_bench: bool = True#
Rescale the benchmark holdings to sum to the sum of the holdings.
- field normalize_holdings: bool = True#
Make holdings sum to one.
- field analytics_space: Literal['absolute', 'active', 'benchmark'] = 'absolute'#
Compute the analytics in absolute space, active space, or compute the analytics only on the benchmark.